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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

Rapid Monitoring and Defense Approach for Resilience Improvement of Grid Cyber Security

Cyber-physical systems and electric utilities significantly depend on the reliability and efficiency of information and operational technology. However, false data injection attacks based on synchrophasor measurement data pose a serious threat to the safe and reliable operation of modern power systems. Here, to mitigate this problem, a rapid monitoring and defense approach is proposed to defend against cyber attacks. Initially, the Time and Frequency based Convolutional neural Network (TFCN) is proposed to detect different types of attacks. Within the TFCN, the advances are that both time and frequency domain information can be fused without extra spectrum analysis methods, and can save detection time to speed the calculation efficiency using the developed time-frequency block. Next, a comprehensive defense strategy is developed for multiple cyber attacks to ensure the stability and resilience of the power system according to the feedback detection results. The advances of this strategy are that different control strategies can be automatically selected to recover the stability to the greatest extent according to the detected attacks. To verify the effectiveness of the proposed approach, the high-speed frequency measurements collected from the wide-area monitoring system are used. The results demonstrate that the cyber attack detection performance can reach 95.57% accuracy, outperforming both traditional and some advanced neural networks. Importantly, the defense strategy is conducted and verified in a modified IEEE 39 bus system as well, which illustrates profound performance in faster stability restoration.

Comprehensive defense strategy↗

FEED Study for Climeworks Direct Air Capture at a California Geothermal Facility with Long-Term Storage (Final Scientific/Technical Report)

The overall objective of the project is to execute and complete a front-end engineering and design (FEED) study of an advanced Direct Air Capture (DAC) and Storage (DAC+S) system that is capable of removing and sequestering a minimum of 5,000 tonne/yr of CO 2 from the air based on cradle-to-gate life cycle assessment (LCA). The project will examine retrofitting and utilizing an existing domestic geothermal resource. The selected DAC system will be technology from Climeworks AG (Climeworks) that consists of an adsorption-desorption process to remove CO 2 from ambient air by using a selective filter. The geothermal host site is operated by Ormat Technologies Inc. (ORMAT). The DAC system will capture CO 2 using thermal energy from the host geothermal resource. This Final Scientific/Technical Report is a collection of the deliverables for the project. The project team was not able to successfully complete all the necessary tasks for this project. Shortly after the start of the project, two (2) project partners removed themselves from the study. The Awardee attempted to find a replacement for the direct air capture technology provider and geothermal energy provider. Due to this the awardee submitted a letter of cancellation for the project, letter is attached in the appendix. No funds were expended during the course of the project.

15 GEOTHERMAL ENERGY↗

Next Generation Energy Training

Report of Activities developing and deploying training designed for the next generation work force for energy efficient and high performance construction.

30 DIRECT ENERGY CONVERSION↗

Construction Methodology Transformation for the Benefit of Workforce Development

Construction is a key economic engine driving both national and global economies. While manual, onsite construction methods dominate the U.S. construction industry, a major shift towards offsite methods has been underway due to its efficiency, speed, and potential cost savings. The workforce necessary for offsite construction growth does not exist in its current form because of the focus on onsite methodologies and the lack of exposure to offsite building methods at all levels of a student’s learning journey. The growth of the U.S. construction industry and competitiveness in an increasingly global construction market over the coming decades can only be supported by a dramatic increase in the use of offsite methods, which requires ramping up workforce training for certain skillsets. The goal of Construction Methodology Transformation for the Benefit of Workforce Development was to understand the opportunities and barriers in both education and industry and to identify best practices for offering curriculum and training to educators, industry, and students that would support skills needed for careers in offsite construction. Our team proposed combining three offsite construction workforce development needs: content development, exposure and training, and job placement - under a single Platform model that would increase experience and career opportunities for students and help match them with potential industry members. Through our proposed solution we expected to see: developed offsite curriculum being utilized by educators and students; an increase in the identification of construction technology and offsite construction methods; an average increase in knowledge gain of at least 25% after participation in pilots; better equipped candidates who are prepared for jobs in offsite construction; and a beta workforce development platform that helps build more pathways for students looking for careers in offsite construction. The two pilots included almost 250 students and resulted in an average knowledge gain of 37 percent. Our research has identified areas of opportunity, for both education and industry to make collaborative training programs more efficient and successful. The chosen techniques for this program are extremely effective when both the school and factory have solid processes and cultures in place to accept students into training programs. This project serves as an important stepping stone to industrywide collaboration to move workforce development for offsite construction forward across the country. With continued collaboration programs like this can provide much needed early exposure and training in offsite construction and we can begin to fill important positions for the future of construction.

99 GENERAL AND MISCELLANEOUS↗

EUREICA: Efficient UltRa Endpoint IoT-enabled Coordinated Architecture

The electricity grid has evolved from a physical system to a cyber-physical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) that include renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. The purpose of this project was to develop a framework ((Efficient, Ultra-REsilient, IoT-Coordinated Assets, or EUREICA)for achieving grid resilience through suitably coordinated assets including a network of Internet of Things (IoT) devices, and a local electricity market (LEM) to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. Experiments conducted during this project demonstrated that, with this SA, a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. The demonstrations were carried out using a variety of high-fidelity co-simulation platforms, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

14 SOLAR ENERGY↗

Artificial Intelligence for Data Center Operations (AIOps): Cooperative Research and Development (Final Report)

High performance computing data centers will increasingly need to rely on automation to keep pace with exascale growth in compute capability and to manage and optimize the data center environment and facility resources. Artificial intelligence and machine learning approaches provide the means to improve HPC data center operational efficiency, by learning historical trends and training models to operate on real-time data collected from both IT and facilities sources. NREL has developed methods of real-time collection, aggregation and streaming of these data in the ESIF HPC Data Center and has collected a significant dataset of relevant metrics across computer systems, racks, environmental, building and utility sources for research into various predictive analytics problems. HPE's Advanced Technology Group (ATG) is doing comprehensive research into exascale monitoring and management for High Performance Computing (HPC) systems (hereinafter HPE's Data Monitoring/ Management Technology). NREL and HPE will collaborate to add Artificial Intelligence (AI) to NREL's real-time data collection/ aggregation/ streaming system and HPE's Data Monitoring/ Management System, with the goal of improving the operational efficiency of NREL's Energy Systems Integration Facility (ESIF) HPC Data Center through data analytics on both historical and real-time data from IT systems and facilities operations. This collaboration will consist of efforts in Data Management, Data Analytics, and AI/ML Optimization for both manual and autonomous intervention in data center operations. This will be a multi-year, multi-staged effort with a goal towards building capabilities for an Advanced Smart Facility, and demonstration of these techniques in the NREL ESIF HPC Data Center.

97 MATHEMATICS AND COMPUTING↗

Particle Physics Division Lifting Fixture Database Restructure

The Particle Physics Division (PPD) at Fermilab needed to modernize its outdated lifting fixture database. Many fixtures lacked identification or had incomplete information. During a summer internship, I cross-referenced existing data, photographed and measured fixtures using standardized tools, and updated their locations and details in a modern Excel format. Some fixtures were identified as belonging to other departments, like the Applied Physics and Superconducting Technology Directorate (APS-TD). This effort significantly improved the accuracy and utility of the PPD database, streamlined other departmental inventories, and potentially saved hundreds of thousands of dollars. The work concluded with a clear, organized record of all verified lifting fixtures.

Creedon, Carroll [Unlisted, US, IL; Fermilab]↗

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Effects of feruloyl-CoA 6'-hydroxylase 1 overexpression on lignin and cell wall characteristics in transgenic hybrid aspen

In plant cell walls, lignin, cellulose, and the hemicelluloses form intricate three-dimensional structures. Owing to its complexity, lignin often acts as a bottleneck for the efficient utilization of polysaccharide components as biochemicals and functional materials. A promising approach to mitigate and/or overcome lignin recalcitrance is the qualitative and quantitative modification of lignin by genetic engineering. Feruloyl-CoA 6'-hydroxylase (F6'H1) is a 2-oxoglutarate-dependent dioxygenase that catalyzes the conversion of feruloyl-CoA, one of the intermediates of the lignin biosynthetic pathway, into 6'-hydroxyferuloyl-CoA, the precursor of scopoletin (7-hydroxy-6-methoxycoumarin). In a previous study with Arabidopsis thaliana, we demonstrated that overexpression of F6'H1 under a xylem-preferential promoter led to scopoletin incorporation into the cell wall. This altered the chemical structure of lignin without affecting lignin content or saccharification efficiency. In the present study, the same F6'H1 construct was introduced into hybrid aspen (Populus tremula × tremuloides T89), a model woody plant, and its effects on plant morphology, lignin chemical structure, global gene expression, and phenolic metabolism were examined. The transgenic plants successfully overproduced scopoletin while exhibiting severe growth retardation, a phenotype not previously observed in Arabidopsis. Scopoletin accumulation was most pronounced in the secondary walls of tracheary elements and the compound middle lamella, with low levels in the fiber cell walls. Overexpression of F6'H1 also affected the metabolism of aromatics, including lignin precursors. Heteronuclear single-quantum coherence (HSQC) NMR spectroscopy revealed that scopoletin in cell walls was bound to lignin, leading to a reduction in lignin content and changes in its monomeric composition and molar mass distribution. Furthermore, the enzymatic saccharification efficiency of the transgenic cell walls was more than three times higher than that of the wild-type plants, even without pretreatment. Although addressing growth inhibition remains a priority, incorporating scopoletin into lignin demonstrates significant potential for improving woody biomass utilization.

59 BASIC BIOLOGICAL SCIENCES↗

Field Demonstration and Adoption Impacts of an Affordable Thermoelectric Heat Pump

This study presents the design, field validation, and utility impacts of an air source heat pump that uses thermoelectric (TE) technology to provide supplemental heating at outside air temperatures below 17°F. Conventional heat pumps experience reduced heating capacity and COP at low outdoor temperatures due to the temperature difference between the source and demand sides of the vapor compression cycle. Consequently, during colder months, supplemental heating such as electric resistance or natural gas furnace is often needed to provide additional warmth, which increases the overall equipment and energy costs. To address this challenge, a TE subcooler (an array of solid-state, thermoelectric modules that provides heat pumping using non-vapor compression technique) is fabricated and integrated with the vapor compression cycle of a conventional air-source heat pump. In colder ambient conditions, TE subcooler exchanges heat with the refrigerant to provide additional subcooling, thereby enhancing the capacity of the heat pump. The operation of thermoelectric-integrated heat pump was demonstrated in an occupied single-family home in Nashville, TN. The TE subcooler increased the system’s heating capacity at 15°F outdoor temperature by 25–30% and reduced electricity demand by 10%. It also met the heating load in the house without supplemental electric resistance down to 5°F outdoors, delivering the additional heat at nearly 80% greater efficiency compared to electric resistance heating. With a modest first cost increment of 10–15% over conventional single-speed heat pumps, this approach offers a promising, energy-efficient solution to accelerate residential heat pump adoption in the U.S.

KRISHNAMOORTHY, Sreenidhi [Electric Power Research↗

Harnessing the Power of AI: Status and Expansion of Current Domestic Transport Security Through Flexible Embedded Hardware

As applications of Artificial Intelligence (AI) continue to expand, there are increasing opportunities to leverage applied AI methodologies with mobile transportation focused embedded systems. Current applications of AI in transportation focus on a variety of areas, including fuel efficiency, safety, security, and other broad fields of optimization or detection. To leverage these AI workflows and methodologies in the field, teams must utilize complex embedded systems capable of implementing these AI-enabled algorithms in real-time. In this paper, we will investigate how these algorithms can be integrated into existing technologies leveraging vehicle data - such as the Controller Area Network Transport Security Tracking and Reporting Unit (C-STAR). The C-STAR technology is an embedded platform with onboard computation capable of running next generation algorithms in vehicle systems AI, such as preventative maintenance, driver authentication, and transport security. As deployed in the field, the C-STAR has a limited AI functionality –this paper will directly discuss how a device like C-STAR can be utilized and the advantages of integrating these new technologies. We will open with relevant background information and transportation projects that leverage AI, focusing specifically on those around transport security such as vehicle identification, anomaly detection, and deterrence. We will then extend this into potential opportunities and scaling for AI methodologies using platforms like the C-STAR. Finally, we will speak directly to the challenges of deploying AI-powered workflows, such as computing power needs, bandwidth, hallucinations, and other regulatory considerations.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS↗

Assessing the Performance and Impact of PV Technologies on Storage in Hybrid Renewable Systems

Traditional monofacial photovoltaic (mPV) systems are commonly adopted and well-documented because of their lower upfront costs in comparison to bifacial photovoltaic (bPV) systems. This study investigates how PV technologies impact energy storage in grid-scale hybrid renewable systems, focusing on optimizing and assessing the performance of mPV and bPV technologies integrated with pumped storage hydropower. Using Ludington City, Michigan as a case study and analyzing real-world data such as solar irradiance, ambient temperature, and utility-scale load profiles, the research highlights the operational and economic benefits of bPV systems. The results reveal that bPV systems can pump approximately 10.38% more water annually to the upper reservoir while achieving a lower levelized cost of energy ($0.0578/kWh for bPV vs. $0.0672/kWh for mPV). This study underscores the outstanding potential of bPV systems in enhancing energy storage and management strategies, contributing to a more sustainable and resilient renewable energy future.

13 HYDRO ENERGY↗

Development of Human and Technology Integration Guidance for Work Optimization and Effective Use of Information

Existing nuclear power contributes to roughly 20% of the total electricity generation, and consistently provides the highest capacity factor of any other electricity generating resource in the United States. Despite these advantages, the existing nuclear power plant fleet in the United States has been enduring significant challenges in providing electricity in a cost-competitive manner, which has ultimately threatened the long-term economic viability of these plants. A major contributor to these increased operating and maintenance costs has been the continued reliance of a large workforce who perform their work under an operating model that has largely remained unchanged since the commissioning of these nuclear power plants. Unfortunately, while this operating model has provided safe and reliable electricity, other industries have already began transforming their workforce through the use of advanced digital technology and automation that has reduced their operating and maintenance cost significantly. In order for the United States nuclear industry to remain economically viable, a similar transformation must be considered in which digital technologies and automation capabilities are brought in to support key plant functions across all work functions across plant operation, maintenance, and support. To effectively integrate digital technology and automation in the existing nuclear power plant operating model, a multidisciplinary approach is needed that addresses technological and sociotechnical (i.e., human and technology integration) considerations. This report describes an extension to the human and technology integration methodology, herein referred to as Human Integration and Technology Task Force for Work Management Optimization (HITT), to support the safe, reliable, and efficient use of proposed innovations with the intended users in their intended environment to perform their intended tasks. By effectively incorporating human and technology integration into a plant modernization effort by using HITT, we believe that a utility can significantly improve work performance and overall workforce quality of life. For instance, if HITT is performed to optimize work management, scheduling performance and scope stability can be improved by up to 10%. HITT enables these benefits through developing a rich understanding of the work being performed, the utility’s vision, and the opportunities that provide greatest value to optimize performance through a 10-step process illustrated below as a quick guide. The quick guide contains links in the righthand side of each step that allows for navigation to the detailed section (Section 4) of HITT in this technical report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

EV Shuttle Bus Pilot

The EV Shuttle Bus Pilot dataset contains data and analysis from Hocking-Athens-Perry Community Action's demonstration of an electric bus on routes of their rural Athens Public Transit system. The vehicle used in the demonstration was a Ford E-450 cutaway equipped with an electric drivetrain, a 127-kWh battery system by Motiv Power Systems, and a cabin upfit by Turtle Top. Data gathered include route assignments, running time and distance, fuel economy, and charge cycles. A comparison of the vehicle's observed duty cycle with duty cycle modeling from other rural transit fleets in the National Transit Database is included to help better understand the rural adoption potential for this fleet technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modular Staged Pressurized Oxy-Combustion (SPOC) Power Plant for Coal and Biomass – Integration of Combustor Boiler and DCC

Utilities and grid operators worldwide are under significant pressure to incorporate intermittent renewable sources while strategizing on how to maintain the necessary stability and reliability of the grid. The development of a power plant which will be capable of flexible operation to meet the needs of the grid as more intermittent sources like wind and solar energy are incorporated is key to maintain the reliability of the grid. Through the use of innovative and cutting-edge technologies that improve efficiency and reduce carbon emissions, and being small compared to today's conventional utility-scale power plants, the modular Staged, Pressurized Oxy-Combustion (SPOC) process envisioned by and under development at Washington University in St. Louis (WUSTL) has the potential to achieve these goals. Specifically, the process offers: 1) a modular plant design that allows for better operational flexibility; 2) the utilization of fuel-staging and pressurized oxy-combustion, resulting in smaller plant size, improved plant efficiency, and reduced costs for pollutant and CO2 removal compared to traditional power plants with post-combustion capture technology; and 3) the use of small modular boilers and pollutant removal units that can be constructed off-site leading to reduced capital costs for the plant. WUSTL is advancing the development of the critical components for the SPOC power plant, including the integrated combustor-boiler system and the direct contact cooler. To demonstrate the boiler convective section and to obtain critical data for commercial-scale pressurized boiler design, a simulated convective heat transfer boiler test section was designed and integrated with the combustor (radiant section). A direct contact cooler (DCC) was integrated with the combustor-boiler to demonstrate the dynamic operation of the integrated system and the performance of the DCC, including the efficiency for simultaneous removal of NOx and SOx. This talk will present an update on the evaluation of the critical components for system integration, including heat transfer data from the simulated boiler, scrubbing efficiency for the DCC under different operating conditions, and CFD modeling and validation for burner and boiler development.

Magalhaes, Duarte↗

Accident Progression and Source Term Demonstration Calculations for the Advanced Burner Test Reactor (ABTR)

As advanced reactor designers approach broad deployment of new reactor technologies and the associated applications, a critical milestone on this path includes licensing or authorization of these designs in the current regulatory environment. Commercial licensing and DOE authorization both consist of numerous aspects to not only certify the designed plant will operate as intended, but also related to confirmation of the safe operation of these facilities that comply with specific standards and requirements. To that end, domestic industry and regulators require toolsets and methods which can be used to confirm that advanced reactor designs not only align with expected performance during normal operation, but also a series of transient scenarios. These codes require a satisfactory validation basis, and in the absence of such a basis, code-to-code comparisons are often utilized as a surrogate to confirm model adequacy. To support this need for fast reactor technologies, a series of analyses using SAS4A/SASSYS- 1 and the Simplified Radionuclide Transport (SRT) code have been conducted for the Advanced Burner Test Reactor (ABTR). These analyses are expected to not only provide a baseline for transient and source term analyses of ABTR, but to also provide context for the key physics that determine evolution of specific transient scenarios in a sodium-cooled fast reactor (SFR). These codes are utilized for this work given their adoption in the SFR industry and by key SFR stakeholders.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗